Counteracting Presentation Attacks in Face, Fingerprint, and Iris Recognition

Pinto, Allan; Pedrini, Hélio; Krumdick, Michael; Becker, Benedict; Czajka, Adam; Bowyer, Kevin W.; Rocha, Anderson

doi:10.1201/b22524-11

Cited by 16 publications

(7 citation statements)

References 1 publication

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“…• good generalization capabilities: since the proposed algorithm is not trained for any specific pattern, and uses a simple observation that textured contact lenses will produce larger shadows than authentic iris when illuminated at different angles, this PAD is agnostic to contact lens brand or specific pattern printed on the lens; this is in general not true for image filtering-based feature extractors (including deep-learning-based solutions), which are known to perform worse in the openset testing scenario [13,15];…”

Section: Discussionmentioning

confidence: 99%

Iris Presentation Attack Detection Based on Photometric Stereo Features

Czajka

Fang

Bowyer

2019

2019 IEEE Winter Conference on Applications of Computer Vision (WACV)

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We propose a new iris presentation attack detection method using three-dimensional features of an observed iris region estimated by photometric stereo. Our implementation uses a pair of iris images acquired by a common commercial iris sensor (LG 4000). No hardware modifications of any kind are required. Our approach should be applicable to any iris sensor that can illuminate the eye from two different directions. Each iris image in the pair is captured under near-infrared illumination at a different angle relative to the eye. Photometric stereo is used to estimate surface normal vectors in the non-occluded portions of the iris region. The variability of the normal vectors is used as the presentation attack detection score. This score is larger for a texture that is irregularly opaque and printed on a convex contact lens, and is smaller for an authentic iris texture. Thus the problem is formulated as binary classification into (a) an eye wearing textured contact lens and (b) the texture of an actual iris surface (possibly seen through a clear contact lens). Experiments were carried out on a database of approx. 2,900 iris image pairs acquired from approx. 100 subjects. Our method was able to correctly classify over 95% of samples when tested on contact lens brands unseen in training, and over 98% of samples when the contact lens brand was seen during training. The source codes of the method are made available to other researchers.

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Section: Discussionmentioning

confidence: 99%

Iris Presentation Attack Detection Based on Photometric Stereo Features

Czajka

Fang

Bowyer

2019

2019 IEEE Winter Conference on Applications of Computer Vision (WACV)

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“…From a security point of view, continuous authentication with various modes faces different challenges. Countermeasures against various attacks on physiological biometrics have been discussed for decades [ 119 , 120 ], but, still, physiological biometrics are not considered secure authentication modes. Behavioral biometric-based approaches also face distinct security vulnerabilities.…”

Section: Security and Privacy Concernsmentioning

confidence: 99%

Security, Privacy, and Usability in Continuous Authentication: A Survey

Baig

Eskeland

2021

Sensors

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Continuous authentication has been proposed as a possible approach for passive and seamless user authentication, using sensor data comprising biometric, behavioral, and context-oriented characteristics. Since these are personal data being transmitted and are outside the control of the user, this approach causes privacy issues. Continuous authentication has security challenges concerning poor matching rates and susceptibility of replay attacks. The security issues are mainly poor matching rates and the problems of replay attacks. In this survey, we present an overview of continuous authentication and comprehensively discusses its different modes, and issues that these modes have related to security, privacy, and usability. A comparison of privacy-preserving approaches dealing with the privacy issues is provided, and lastly recommendations for secure, privacy-preserving, and user-friendly continuous authentication.

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“…Many biometric techniques are available in the authentication process such as finger print recognition, eye pattern recognition, face recognition, voice pattern recognition, vein recognition and others. However, the fingerprint pattern recognition remains the most used technique for its simplicity of use of and cost effective [15][16][17]. The facial recognition is also considered as a good alternative to fingerprint since no physical interaction with the user is required and the results of matching are accurate if the image is well captured [18].…”

Section: Basics and Access Controlmentioning

confidence: 99%

Multimodal access control system combining RFID, fingerprint and facial recognition

Beqqal

Azizi

Lanet

2020

IJEECS

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<span>Monomodal biometry does not constitute an effective measure to meet the desired performance requirements for large-scale applications, due to limita-tions such as noisy data, restricted degree of freedom and unacceptable error rates. Some of these problems can be solved through multimodal biometric systems that involve using a combination of two or more biometric modali-ties in a single identification system. Identification based on multiple biomet-rics represents an emerging trend. The reason for combining different modal-ities is to improve the recognition rate. In practice, multi-biometric aims to reduce the False Acceptance Ratio (FAR) and False Rejection Ratio (FRR) which are two standard metrics widely used in the accuracy of biometric sys-tems. In this paper, we will examine the different possible scenario in multi-modal biometric systems using RFID, fingerprint and facial recognition, that can be adopted to merge information and improve the overall accuracy of the system.</span>

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Counteracting Presentation Attacks in Face, Fingerprint, and Iris Recognition

Cited by 16 publications

References 1 publication

Iris Presentation Attack Detection Based on Photometric Stereo Features

Iris Presentation Attack Detection Based on Photometric Stereo Features

Security, Privacy, and Usability in Continuous Authentication: A Survey

Multimodal access control system combining RFID, fingerprint and facial recognition

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